Showing 2,361 - 2,380 results of 5,254 for search 'significantly ((linear decrease) OR (((mean decrease) OR (greater decrease))))', query time: 0.28s Refine Results
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    Major hyperparameters of RF-SVR. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  4. 2364

    Pseudo code for coupling model execution process. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  5. 2365

    Major hyperparameters of RF-MLPR. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  6. 2366

    Results of RF algorithm screening factors. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  7. 2367

    Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
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    Attitude towards NTDs in the study Area. by Uchechukwu M. Chukwuocha (6685790)

    Published 2025
    “…<div><p>Background</p><p>Neglected Tropical Diseases (NTDs) continue to significantly impact marginalized communities, contributing to high morbidity, stigma, and social exclusion. …”
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    Dataset of results. by Uchechukwu M. Chukwuocha (6685790)

    Published 2025
    “…<div><p>Background</p><p>Neglected Tropical Diseases (NTDs) continue to significantly impact marginalized communities, contributing to high morbidity, stigma, and social exclusion. …”
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    Respondents’ perception about the public artwork. by Uchechukwu M. Chukwuocha (6685790)

    Published 2025
    “…<div><p>Background</p><p>Neglected Tropical Diseases (NTDs) continue to significantly impact marginalized communities, contributing to high morbidity, stigma, and social exclusion. …”
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